Mining is a strange sort of industry. It is actually a cluster of processes that enables the world to obtain materials and minerals that cannot be created or manufactured or grown through agriculture. By definition it is the extraction and management of minerals from the earth’s surface, and it has been the core industry of most economies in the world.
Sustainability has in recent years become the biggest dilemma the mining industry faces. The most worrying factors are: Environmental regulations and nationalism have created a major impact. Resources are becoming scarce and more costly to access. Shortage of skilled labor is another major concern.
The commodity boom peaked just over a decade ago. Since then the headwinds have been growing in strength. The mining industry has been forced to re-calibrate and re-think. Some of the key recalibration action points revolve around these aspects
One of the recent advances in Artificial Intelligence technologies is AI Vision, also known as Computer Vision, which enable systems to derive information from visual inputs and use that information to take action or recommend actions. This technology has proved itself by improving safety and efficiency, reducing costs and also providing a host of alerts and insights that have helped businesses turn the corner in other. AI Vision is well positioned now to make a huge difference in various mining processes.
Automating Equipment Operations – AI Vision algorithms help to automate trucks and excavators used for extracting minerals or for automating the process in drilling for ore. Increase in yield through automation sets the tone for a steady improvement in overall productivity by reducing the need for human operators, saving time and money, and improving safety. Cameras equipped with AI Vision can be applied to all sorts of processes including those using heavy machinery. The AI application can streamline ore segregation, assessment of ore fragmentation, site inspection of open pit mines and even underground mines.(Sample Reference videos: https://cogniphi.com/videos/)
Mineral Detection – Intelligent cameras can spot and identify the minerals in the ground, allowing for accurate planning and operations. The software also learns to estimate even the grade of ore in a mine.
Reducing Wastage – Automated ore sorting technology can be used to separate ore from waste rock more quickly and accurately than manual sorting, thus decreasing the amount of waste rock to be processed. An effective sorting/filtering mechanism improves efficiency a great deal.
Monitoring Environmental Impact – Detecting and tracking changes in landscapes, water quality, air quality and land degradation through pattern recognition techniques help to manage and comply with regulations and damages. Even the presence of hazardous materials like Asbestos can be detected, which helps to avoid its exposure to workers on site and also reduces possibility of environmental damage.
Real time Monitoring of Operations – Identifying potential hazards and alerting operators of possible rock falls, equipment malfunctioning, etc helps prevent accidents and reduce safety risks. Monitoring of safety equipment usage by workers becomes a routine affair as cameras will detect and alert any violation of such protocols. Vision AI will also be the supreme Incident Manager, by alerting incidents involving injuries to workers, commotions, etc and unauthorized intrusions or suspicious movements, particularly at night.
Tracking of Goods Movement – Vision-enhanced GPS-based tracking of goods and transport enables real time transit information of materials and implements to and from excavation sites as well as outward shipments of minerals to destinations.
Aerial Surveys of Mining Sites – Drones equipped with cameras powered by AI Vision capabilities can provide detailed and accurate data and mapping of the site’s geological features and the topography, which often are critical to the overall planning and optimization of the operations, as well as for formulating efficient navigation protocols.
Preventive maintenance – AI Vision with Machine Learning algorithms can detect imminent equipment failure and predict when maintenance will be required. This helps reduce downtime and enhances equipment life span and saves on maintenance costs.
Restoration – By detecting and monitoring land degradation caused by the mining, areas that need to be restored early can be prioritized so that further damage is prevented.
Using AI Vision, the Mining industry stands to gain immensely by monitoring environmental factors and reduce their impact on the business, as also improve their sustainability and save money in the long run. Mining will have to upgrade itself to stay relevant. Many economies will suffer if it doesn’t.
Cogniphi is a technology company that enables customers to achieve transformational outcomes through cognitive digital solutions. Cogniphi’s platform AI Vision integrates Computer Vision, Machine Learning, and AI to extract precise and meaningful data from visual footage. These are further converted into actionable insights and notifications.